Anonymous evaluation and delayed feedback social interaction method, device and computer equipment

By separating the evaluation stage in the social interaction system and employing zero-knowledge proof and time-lock encryption technologies, anonymous evaluation data collection and delayed access control are achieved, solving the problems of evaluator identity exposure and evaluation data distortion, and improving the authenticity of the evaluation and the fairness of the system.

CN122413451APending Publication Date: 2026-07-17SHENZHEN YINLIAN TECHNOLOGY CO LTD

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHENZHEN YINLIAN TECHNOLOGY CO LTD
Filing Date
2026-04-15
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

In existing social interaction systems, the exposure of evaluators' identities leads to evaluation bias, and the lack of thoughtful consideration and solidified protection results in a lack of closed-loop optimization mechanisms, resulting in distorted evaluation data and a decline in system fairness.

Method used

By separating the social interaction phase from the evaluation collection phase, and employing zero-knowledge proof and time-lock encryption technologies, anonymous evaluation data collection and delayed access control are achieved. Aggregated evaluation results are generated and pushed out, and an entry point for objection feedback is provided to dynamically optimize user profile weights.

Benefits of technology

Significantly improve the authenticity and collection rate of evaluations, ensure the independence and immutability of evaluations, achieve fair and traceable feedback and system adaptive optimization, and enhance the system's impartiality and resistance to attacks.

✦ Generated by Eureka AI based on patent content.

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Abstract

本发明属于信息处理技术领域,涉及一种匿名评价与延迟反馈社交交互方法、装置及计算机设备,所述方法包括:将社交互动阶段与评价采集阶段进行分离;基于零知识证明,采集匿名评价数据,将所述评价数据与评价者身份剥离;基于时间锁加密,进行延迟访问控制与评价数据固化;在延迟期满后对已固化的匿名评价数据进行聚合处理,生成反映群体意见的统计结果;将生成的聚合评价结果推送至被评价者终端,并提供异议反馈入口;基于异议反馈,进行画像权重动态优化与系统闭环。显著提升评价的真实性与采集率,保障评价的独立性与不可篡改性,实现公平、可追溯的聚合反馈与系统自适应优化。
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